The tracking of user activities increases over the holidays. A user is either a device (car, phone, tablet, etc.), a person (shopping online or off), or a thing (a credit card, etc.) The goal is to offer the users and the owners of the devices and things opportunities to buy more, to shop more, to be tracked more. It is an opportunity, one which normal people cannot avoid. A recent holiday saw the same things coming into my mailbox that show up every Monday, but each web visit led somewhere else.
Big data drives nearly everything we see on websites these days. Take Google. What I browse for in my city and state has a different result set than if I were in a different city and state. It also has a different result set based on who I am (as determined by some form of algorithm). To handle the millions of result sets that are different, Google relies upon big data. Google has also made the underlying technology for such analysis available to others (see My Thoughts on the Google Horizon Event). These are tools that never sleep, that handle the uptick of web-based services over the holidays with aplomb.
There are other services that get an uptick just before holidays, and even during them as well. Coupon creation picks up. The goal is to get you into the store, or the web store, to make a purchase with these other opportunities. There are whole companies that just create coupons—perhaps the ones that appear when they sense you walking by (yes, they detect your electronic signature and create a coupon just for you). Or perhaps they are the ones that show up a day or two before the holiday. These are busy times for such companies.
Big data is not just about targeted advertisement. It is also for reviewing hundreds of thousands of sensors around a city, region, and possibly state. The goals of such sensors is to determine the best way to handle the foot, pedal, and car traffic into and out of the city; the best routes for emergency services; and the need for extended parking or more train runs. Monitoring a city is a complex task, and some cities are capable, but others still have to do this by hand. Even so, the number of sensors, cameras, and whatnot that are available in any city is phenomenal today.
Banks also make use of these devices. They need to make sure there is enough money in the ATMs and at the tellers near events. A holiday implies lots of planning. After so many years, many businesses have a grasp of holiday traffic and function. Big data just backs this up, but with new insights. These insights include the following:
- impact of weather on traffic
- impact of other events on traffic
- impact of hotel bookings on events
- impact of weather on available water at outdoor events (not just for humans, but pets)
The list is endless. Once big data is asked its first question about a holiday, others come to mind. Organizations looking to grasp these new methods will ask their first question, one for which they believe they know the correct answer. If the answer differs, then either the question was poorly formulated or the data is incomplete, or perhaps there is a new insight into the business.
Big data works hard in the lead-up to the holiday, during the holiday, and after the holiday. The “after” work includes the handling of all the returns and deliveries, the cleanup of the site for a holiday event, and similar tasks. Delivery services like UPS and FedEx track everything about a delivery, including the truck and even the driver. Returns are tracked not only in order to schedule staffing, but also to determine what items are more likely to be returned than others. This helps the business decide whether to continue to stock those items in the future, change their advertisements, or even change their construction.
No matter how you look at it, big data is in use around us. It is tracking everything we do. Even if you pay with cash, you can still be tracked via other forms of sensors. At the moment, we can only hope this is for the good. Yes, we should think about how big data is used within our environments, what is tracked, and what questions we should ask ask.
There are many ways to get started. There are many technologies to use. To compete these days, you need to start somewhere and progress quickly to have a data-centric business with technology chosen to support it. You may just want to use Google or other cloud-based big data solutions. You may want to start small with a local tool to read data and do your own inquiries. What Google does is really at one end of the spectrum, Splunk and Elasticsearch being at the other. The real question is “What is your question?” Know that before you choose a tool. The corollary of that first question is to understand how that answer impacts others. What are the privacy concerns around asking your question?
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